mouse tibia
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PAIN Reports ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. e950
Author(s):  
Jason R. Wickman ◽  
Xuan Luo ◽  
Wenwu Li ◽  
Renee Jean-Toussaint ◽  
Peyman Sahbaie ◽  
...  

2021 ◽  
Vol 8 (6) ◽  
pp. 201401
Author(s):  
A. A. Felder ◽  
S. Monzem ◽  
R. De Souza ◽  
B. Javaheri ◽  
D. Mills ◽  
...  

Changes in trabecular micro-architecture are key to our understanding of osteoporosis. Previous work focusing on structure model index (SMI) measurements have concluded that disease progression entails a shift from plates to rods in trabecular bone, but SMI is heavily biased by bone volume fraction. As an alternative to SMI, we proposed the ellipsoid factor (EF) as a continuous measure of local trabecular shape between plate-like and rod-like extremes. We investigated the relationship between EF distributions, SMI and bone volume fraction of the trabecular geometry in a murine model of disuse osteoporosis as well as from human vertebrae of differing bone volume fraction. We observed a moderate shift in EF median (at later disease stages in mouse tibia) and EF mode (in the vertebral samples with low bone volume fraction) towards a more rod-like geometry, but not in EF maximum and minimum. These results support the notion that the plate to rod transition does not coincide with the onset of bone loss and is considerably more moderate, when it does occur, than SMI suggests. A variety of local shapes not straightforward to categorize as rod or plate exist in all our trabecular bone samples.


Author(s):  
S. Oliviero ◽  
M. Roberts ◽  
R. Owen ◽  
G. C. Reilly ◽  
I. Bellantuono ◽  
...  

AbstractNew treatments for bone diseases require testing in animal models before clinical translation, and the mouse tibia is among the most common models. In vivo micro-Computed Tomography (microCT)-based micro-Finite Element (microFE) models can be used for predicting the bone strength non-invasively, after proper validation against experimental data. Different modelling techniques can be used to estimate the bone properties, and the accuracy associated with each is unclear. The aim of this study was to evaluate the ability of different microCT-based microFE models to predict the mechanical properties of the mouse tibia under compressive load. Twenty tibiae were microCT scanned at 10.4 µm voxel size and subsequently compressed at 0.03 mm/s until failure. Stiffness and failure load were measured from the load–displacement curves. Different microFE models were generated from each microCT image, with hexahedral or tetrahedral mesh, and homogeneous or heterogeneous material properties. Prediction accuracy was comparable among models. The best correlations between experimental and predicted mechanical properties, as well as lower errors, were obtained for hexahedral models with homogeneous material properties. Experimental stiffness and predicted stiffness were reasonably well correlated (R2 = 0.53–0.65, average error of 13–17%). A lower correlation was found for failure load (R2 = 0.21–0.48, average error of 9–15%). Experimental and predicted mechanical properties normalized by the total bone mass were strongly correlated (R2 = 0.75–0.80 for stiffness, R2 = 0.55–0.81 for failure load). In conclusion, hexahedral models with homogeneous material properties based on in vivo microCT images were shown to best predict the mechanical properties of the mouse tibia.


2020 ◽  
Author(s):  
A. A. Felder ◽  
S. Monzem ◽  
R. De Souza ◽  
B. Javaheri ◽  
D. Mills ◽  
...  

Changes in trabecular micro-architecture are key to our understanding of osteoporosis. Previous work focusing on structure model index (SMI) measurements have concluded that disease progression entails a shift from plates to rods in trabecular bone, but SMI is heavily biased by bone volume fraction. As an alternative to SMI, Ellipsoid Factor (EF) has been proposed as a continuous measure of local trabecular shape between plate-like and rod-like extremes. We investigated the relationship between EF distributions, SMI and bone volume fraction of the trabecular geometry in a murine model of disuse osteoporosis as well as from human vertebrae of differing bone volume fraction. We observed a moderate shift in EF median (at later disease stages in mouse tibia) and EF mode (in the vertebral samples with low bone volume fraction) towards a more rod-like geometry, but not in EF maximum and minimum. These results support the notion that the plate to rod transition does not coincide with the onset of bone loss and is considerably more moderate, when it does occur, than SMI suggests. A variety of local shapes not straightforward to categorise as rod or plate exist in all our trabecular bone samples.Subject Areasosteoporosis, trabecular bone, morphometry


2019 ◽  
Vol 19 (3) ◽  
pp. 985-1001 ◽  
Author(s):  
Vee San Cheong ◽  
Ana Campos Marin ◽  
Damien Lacroix ◽  
Enrico Dall’Ara

AbstractUnderstanding how bone adapts to mechanical stimuli is fundamental for optimising treatments against musculoskeletal diseases in preclinical studies, but the contribution of physiological loading to bone adaptation in mouse tibia has not been quantified so far. In this study, a novel mechanistic model to predict bone adaptation based on physiological loading was developed and its outputs were compared with longitudinal scans of the mouse tibia. Bone remodelling was driven by the mechanical stimuli estimated from micro-FEA models constructed from micro-CT scans of C57BL/6 female mice (N = 5) from weeks 14 and 20 of age, to predict bone changes in week 16 or 22. Parametric analysis was conducted to evaluate the sensitivity of the models to subject-specific or averaged parameters, parameters from week 14 or week 20, and to strain energy density (SED) or maximum principal strain (εmaxprinc). The results at week 20 showed no significant difference in bone densitometric properties between experimental and predicted images across the tibia for both stimuli, and 59% and 47% of the predicted voxels matched with the experimental sites in apposition and resorption, respectively. The model was able to reproduce regions of bone apposition in both periosteal and endosteal surfaces (70% and 40% for SED and εmaxprinc, respectively), but it under-predicted the experimental sites of resorption by over 85%. This study shows for the first time the potential of a subject-specific mechanoregulation algorithm to predict bone changes in a mouse model under physiological loading. Nevertheless, the weak predictions of resorption suggest that a combined stimulus or biological stimuli should be accounted for in the model.


PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0225127 ◽  
Author(s):  
Sara Oliviero ◽  
Mario Giorgi ◽  
Peter J. Laud ◽  
Enrico Dall’Ara
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